How do you control what AI agents are allowed to do?

[Tormen]

We’ve moved a few internal AI agents beyond the experimental stage, and security is starting to ask questions we didn’t really have to think about during the pilot. Some agents can query internal databases, others can call external APIs or work with company repositories, but the access rules were added at different times by different teams. Now we need a reliable way to control who can use each agent, what systems it can reach, and keep a record when those permissions change. How are companies handling this once agents start getting real access to production resources?

[Davidian]

Old permissions have a nasty habit of sticking around long after everyone has forgotten why they were granted. I’d treat agent access much like service accounts: give every agent a clear owner, keep permissions as narrow as possible, and require approval whenever somebody adds a new tool or data source. Put those policies under version control too, so a permission change goes through the same review process as code and nobody can quietly expand access from a dashboard.

[Howkard]

Security usually gets a lot less nervous when there’s one place to answer who has access, what changed, and when it changed. That’s the point where scattered permissions stop being a team-by-team problem and need some structure around them. You can look at AI agent governance here: https://agyn.io/ . Centralizing those controls gives security a cleaner view of permissions, connected resources, and change history. It also makes future access reviews much less of a scavenger hunt.